DEA-C02 Data Movement Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  A scheduled COPY INTO statement executed every minute by a Snowflake TASK.

  Why it's wrong here

  A TASK that runs COPY INTO every minute introduces at least one minute of latency and repeatedly scans the stage for new files, which is inefficient for hundreds of small files arriving per minute. It also consumes warehouse credits on every run and cannot match the event-driven responsiveness of Snowpipe.

• ✗

  A Snowflake STREAM on the target table combined with a TASK to poll the S3 bucket.

  Why it's wrong here

  STREAM objects capture change data on Snowflake tables, not files in an external S3 bucket, so they cannot detect newly arrived S3 objects. A TASK polling the bucket would still require a COPY INTO load step and would not provide the near-zero latency event-driven behavior needed here.

• ✓

  Snowpipe with AUTO_INGEST = TRUE on the pipe, using a storage integration and an S3 event notification to an SQS queue.

  Why this is correct

  Snowpipe with AUTO_INGEST uses an S3 event notification delivered to an SQS queue that Snowflake manages, and the pipe's COPY statement loads each new file as it lands. This provides the low-latency, event-driven ingestion required for hundreds of small files per minute without scheduling batch jobs.

• ✗

  An external table over the S3 stage with automatic refresh using METADATA$FILENAME.

  Why it's wrong here

  External tables expose file data as queryable rows but do not ingest data into a Snowflake table, and their refresh is metadata-driven rather than a true continuous load. For hundreds of small files per minute, querying an external table would also incur repeated parsing overhead and would not populate the target table.